Network modulation in the treatment of Parkinson's disease

Dopamine-responsive post-anoxic parkinsonism

BackgroundParkinsonism following hypoxic ischemic damage of the basal ganglia is an uncommon phenomenon that has been infrequently reported. However, only a few cases have noted improvement of symptoms with dopaminergic therapy. We report the clinical and imaging features of five patients with post-anoxic parkinsonism responsive to dopamine supplementation.ObjectiveTo describe a retrospective case series of five cases of dopamine-responsive post-anoxic parkinsonism.MethodsWe identified all the cases using the Mayo Clinic Data Management System utilizing advanced data explorer search engine for any patients evaluated for post anoxic parkinsonism and its associated acronyms from 2000-2024. Clinical features, neuroimaging, medication trials, and responses were obtained from chart review of identified patients.ResultsFive patients met the inclusion criteria. All patients underwent anoxic events followed by development of parkinsonism. Patients exhibited parkinsonism described as combinations of bradykinesia, rigidity, tremor, and postural instability. All patients underwent evaluation by a neurologist, MRI imaging, and treatment by dopaminergic agents. Of the five patients, four received carbidopa/levodopa whereas one received a dopamine agonist. All patients were clinically followed for a median of approximately 4 years and showed improvement in parkinsonism.ConclusionsParkinsonism following a hypoxic ischemic insult is a rare occurrence but response to dopaminergic therapy in those cases is even more scarcely described. Our cases series provides important implications for treatment options for patients with post anoxic parkinsonism.

Emerging fiber-based neural interfaces with conductive composites

Neural interfaces that enable bidirectional communication between neural systems and external devices are crucial for treating neurological disorders and advancing brain-machine interfaces. Key requirements for these neural interfaces are the ability to modulate electrophysiological activity without causing tissue damage in the nerve system and long-term usability. Recent advances in biomedical neural electrodes aim to reduce mechanical mismatch between devices and surrounding tissues/organs while maintaining their electrical conductivity. Among these, fiber electrodes stand out as essential candidates for future neural interfaces owing to their remarkable flexibility, controllable scalability, and facile integration with systems. Herein, we introduce fiber-based devices with conductive composites, along with their fabrication technologies, and integration strategies for future neural interfaces. Compared to conventional neural electrodes, fiber electrodes readily combine with conductive materials such as metal nanoparticles, carbon-based nanomaterials, and conductive polymers. Their fabrication technologies enable high electrical performance without sacrificing mechanical properties. In addition, the neural modulation techniques of fiber electrodes; electrical, optical, and chemical, and their applications in central and peripheral nervous systems are carefully discussed. Finally, current limitations and potential advancements in fiber-based neural interfaces are highlighted for future innovations.

Correlation of Parkinson's disease severity and 18F-FDG and 18F-FP-DTBZ PET

Background

Positron emission tomography (PET) using the tracer 18F-fluorodeoxyglucose (18F-FDG) and [18F] 9-fluoropropyl-(+)-dihydrotetrabenazine (18F-FP-DTBZ) is widely utilized to measure metabolic activity and dopaminergic integrity in neurodegenerative diseases such as Parkinson's disease (PD). Previous studies employing 18F-FDG PET have primarily focused on motor or non-motor symptoms, rather than the severity of PD. This study aimed to measure the glucose metabolism of 18F-FDG and the dopaminergic function of 18F-FP-DTBZ across various Hoehn-Yahr (H&Y) stages, analyzing the correlation between metabolic activity, dopaminergic function, and H&Y stages to monitor the severity of PD.

Methods

The cross-sectional study recruited 78 PD patients in 3 groups of H&Y stages I, II, and III-V and 18 healthy control (HC) participants to undergo 18F-FDG and 18F-FP-DTBZ PET scans. Differences in cerebral metabolism and dopaminergic function between groups were evaluated using Student's t-test and Mann-Whitney U test. Moreover, Pearson correlation analysis was used to explore the association between cerebral metabolism, dopaminergic function, and H&Y stages in all patients.

Results

Patients with PD exhibited significant hypometabolic activity in the frontal cortex and relative hypermetabolic activity in the putamen, globus pallidus, thalamus, and cerebellum when compared to HC individuals (P<0.05). Further imaging-clinical correlation research depicted the negative correlation between the metabolic activity in the frontal and putamen regions with H&Y stage. Furthermore, the 18F-FP-DTBZ binding reductions were 18.6%, 46.6%, and 56.9% for the caudate, anterior putamen, and posterior putamen at H&Y stages I; 36.0%, 56.9%, and 65.9% at H&Y stages II; and 41.2%, 61.9%, and 68.5% at H&Y stages III-V, respectively. The 18F-FP-DTBZ binding of caudate, anterior putamen, and posterior putamen exhibited significantly negative correlations to H&Y stage.

Conclusions

In PD, 18F-FDG and 18F-FP-DTBZ PET imaging represent potential biomarkers for tracking metabolic activity and dopaminergic degeneration, offering valuable insights into estimating the severity of disease.

Emerging Techniques for the Personalization of Deep Brain Stimulation Programming

The success of deep brain stimulation (DBS) relies on applying carefully titrated therapeutic stimulation at specific targets. Once implanted, the electrical stimulation parameters at each electrode contact can be modified. Iteratively adjusting the stimulation parameters enables testing for the optimal stimulation settings. Due to the large parameter space, the currently employed empirical testing of individual parameters based on acute clinical response is not sustainable. Within the constraints of short clinical visits, optimization is particularly challenging when clinical features lack immediate feedback, as seen in DBS for dystonia and depression and with the cognitive and axial side effects of DBS for Parkinson's disease. A personalized approach to stimulation parameter selection is desirable as the increasing complexity of modern DBS devices also expands the number of available parameters. This review describes three emerging imaging and electrophysiological methods of personalizing DBS programming. Normative connectome-base stimulation utilizes large datasets of normal or disease-matched connectivity imaging. The stimulation location for an individual patient can then be varied to engage regions associated with optimal connectivity. Electrophysiology-guided open- and closed-loop stimulation capitalizes on the electrophysiological recording capabilities of modern implanted devices to individualize stimulation parameters based on biomarkers of success or symptom onset. Finally, individual functional MRI (fMRI)-based approaches use fMRI during active stimulation to identify parameters resulting in characteristic patterns of functional engagement associated with long-term treatment response. Each method provides different but complementary information, and maximizing treatment efficacy likely requires a combined approach.

Brain network and energy imbalance in Parkinson's disease: linking ATP reduction and α-synuclein pathology

Parkinson's disease (PD) involves the disruption of brain energy homeostasis. This encompasses broad-impact factors such as mitochondrial dysfunction, impaired glycolysis, and other metabolic disturbances, like disruptions in the pentose phosphate pathway and purine metabolism. Cortical hubs, which are highly connected regions essential for coordinating multiple brain functions, require significant energy due to their dense synaptic activity and long-range connections. Deficits in ATP production in PD can severely impair these hubs. The energy imbalance also affects subcortical regions, including the massive axonal arbors in the striatum of substantia nigra pars compacta neurons, due to their high metabolic demand. This ATP decline may result in α-synuclein accumulation, autophagy-lysosomal system impairment, neuronal network breakdown and accelerated neurodegeneration. We propose an "ATP Supply-Demand Mismatch Model" to help explain the pathogenesis of PD. This model emphasizes how ATP deficits drive pathological protein aggregation, impaired autophagy, and the degeneration of key brain networks, contributing to both motor and non-motor symptoms.

[The effect of bilateral subthalamic nucleus deep brain stimulation on gait and balance in patients with Parkinson's disease]

Deep stimulation of the subthalamic nucleus (DBS STN) is a highly effective and relatively safety method of surgical treatment of Parkinson's disease (PD), which can significantly reduce the motor symptoms of the disease (rigidity, tremor, hypokinesia), as well as levodopa-associated dyskinesia and fluctuations. However, the effect of DBS STN on axial symptoms, such as gait and postural stability, remains contentious. The searching for risk factors for worsening gait and balance disturbances in patients receiving DBS STN continues. Studies are being perfomed on the parameters of the DBS STN to reduce its negative impact on gait and balance.

A framework for translational therapy development in deep brain stimulation

Deep brain stimulation (DBS) is an established treatment for motor disorders like Parkinson's disease, but its mechanisms and effects on neurons and networks are not fully understood, limiting research-driven progress. This review presents a framework that combines neurophysiological insights and translational research to enhance DBS therapy, emphasizing biomarkers, device technology, and symptom-specific neuromodulation. It also examines the role of animal research in improving DBS, while acknowledging challenges in clinical translation.

SNMMI Procedure Standard/EANM Practice Guideline for Brain [18F]FDG PET Imaging, Version 2.0

PREAMBLEThe Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional nonprofit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The EANM was founded in 1985. SNMMI and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine.The SNMMI and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated.Each practice guideline, representing a policy statement by the SNMMI/EANM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized.These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, both the SNMMI and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question.The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines.The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment.Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.

PET-based brain molecular connectivity in neurodegenerative disease

PURPOSE OF REVIEW

Molecular imaging has traditionally been used and interpreted primarily in the context of localized and relatively static neurochemical processes. New understanding of brain function and development of novel molecular imaging protocols and analysis methods highlights the relevance of molecular networks that co-exist and interact with functional and structural networks. Although the concept and evidence of disease-specific metabolic brain patterns has existed for some time, only recently has such an approach been applied in the neurotransmitter domain and in the context of multitracer and multimodal studies. This review briefly summarizes initial findings and highlights emerging applications enabled by this new approach.

RECENT FINDINGS

Connectivity based approaches applied to molecular and multimodal imaging have uncovered molecular networks with neurodegeneration-related alterations to metabolism and neurotransmission that uniquely relate to clinical findings; better disease stratification paradigms; an improved understanding of the relationships between neurochemical and functional networks and their related alterations, although the directionality of these relationships are still unresolved; and a new understanding of the molecular underpinning of disease-related alteration in resting-state brain activity.

SUMMARY

Connectivity approaches are poised to greatly enhance the information that can be extracted from molecular imaging. While currently mostly contributing to enhancing understanding of brain function, they are highly likely to contribute to the identification of specific biomarkers that will improve disease management and clinical care.

Deep Brain Stimulation Modulates the Visual Pathway to Improve Freezing of Gait in Parkinson's Disease Patients

OBJECTIVE

To investigate the involvement of the visual cortex in improving freezing of gait (FoG) after subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) patients using whole-brain seed-based functional connectivity.

METHODS

A total of 66 PD patients with FoG who underwent bilateral STN-DBS were included in our study. Patients were divided into a FoG responder group and an FoG nonresponder group according to whether FoG improved 1 year after DBS. We compared the differences in clinical characteristics, brain structural imaging, and seed-based functional connectivity between the 2 groups. The locations of active contacts were further analyzed.

RESULTS

All PD patients benefited from STN-DBS. No significant differences in the baseline characteristics or brain structures were found between the 2 groups. Seed-based functional connectivity analysis revealed that better connectivity in bilateral primary visual areas was associated with better clinical improvement in FoG (P < 0.05 familywise error corrected). Further analysis revealed that this disparity was associated with the location of the active contacts within the rostral region of the sensorimotor subregion in the FoG responder group, in contrast to the findings in the FoG nonresponder group.

CONCLUSIONS

This study suggested that DBS in the rostral region of the STN sensorimotor subregion may alleviate FoG by strengthening functional connectivity in primary visual areas, which has significant implications for guiding surgical strategies for FoG in the future.

Optogenetic fMRI reveals therapeutic circuits of subthalamic nucleus deep brain stimulation

While deep brain stimulation (DBS) is widely employed for managing motor symptoms in Parkinson's disease (PD), its exact circuit mechanisms remain controversial. To identify the neural targets affected by therapeutic DBS in PD, we analyzed DBS-evoked whole brain activity in female hemi-parkinsonian rats using functional magnetic resonance imaging (fMRI). We delivered subthalamic nucleus (STN) DBS at various stimulation pulse repetition rates using optogenetics, allowing unbiased examination of cell-type specific STN feedforward neural activity. Unilateral optogenetic STN DBS elicited pulse repetition rate-dependent alterations of blood-oxygenation-level-dependent (BOLD) signals in SNr (substantia nigra pars reticulata), GP (globus pallidus), and CPu (caudate putamen). Notably, this modulation effectively ameliorated pathological circling behavior in animals expressing the kinetically faster Chronos opsin, but not in animals expressing ChR2. Furthermore, mediation analysis revealed that the pulse repetition rate-dependent behavioral rescue was significantly mediated by optogenetic DBS induced activity changes in GP and CPu, but not in SNr. This suggests that the activation of GP and CPu are critically involved in the therapeutic mechanisms of STN DBS.

Cortico-cortical connectivity is influenced by levodopa in tremor-dominant Parkinson's disease

Resting tremor is the most common presenting motor symptom in Parkinson's disease (PD). The supplementary motor area (SMA) is a main target of the basal-ganglia-thalamo-cortical circuit and has direct, facilitatory connections with the primary motor cortex (M1), which is important for the execution of voluntary movement. Dopamine potentially modulates SMA and M1 activity, and both regions have been implicated in resting tremor. This study investigated SMA-M1 connectivity in individuals with PD ON and OFF dopamine medication, and whether SMA-M1 connectivity is implicated in resting tremor. Dual-site transcranial magnetic stimulation was used to measure SMA-M1 connectivity in PD participants ON and OFF levodopa. Resting tremor was measured using electromyography and accelerometry. Stimulating SMA inhibited M1 excitability OFF levodopa, and facilitated M1 excitability ON levodopa. ON medication, SMA-M1 facilitation was significantly associated with smaller tremor than SMA-M1 inhibition. The current findings contribute to our understanding of the neural networks involved in PD which are altered by levodopa medication and provide a neurophysiological basis for the development of interventions to treat resting tremor.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response

Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.

Impact of Acute Dopamine Replacement on Cognitive Function in Parkinson's Disease

BACKGROUND

PD causes striatal dopaminergic denervation in a posterior/dorsal to anterior/ventral gradient, leaving motor and associative cortico-striato-pallido-thalamic loops differentially susceptible to hyperdopaminergic effects with treatment. As the choice and titration of symptomatic PD medications are guided primarily by motor symptoms, it is important to understand their cognitive implications.

OBJECTIVE

To investigate the effects of acute dopaminergic medication administration on executive function in Parkinson's disease (PD).

METHODS

Participants with idiopathic PD were administered the oral Symbol Digit Modalities Test (SDMT; n = 181) and the Stroop test (n = 172) in the off-medication and "best on" medication states. ANCOVA was used to test for differences between off-medication and on-medication scores corrected for age and years of education.

RESULTS

After administration of symptomatic medications, scores worsened on the SDMT (F = 11.70, P < 0.001, d = -0.13), improved on the Stroop color (F = 26.89, P < 0.001, d = 0.184), word (F = 6.25, P = 0.013, d = 0.09), and color-word (F = 13.22, P < 0.001, d = 0.16) test components, and the Stroop difference and ratio-based interference scores did not significantly change. Longer disease duration correlated with lower scores on the SDMT, Stroop color, word, and color-word scores; however, longer disease duration and higher levodopa-equivalents correlated with higher Stroop difference-based interference scores.

CONCLUSIONS

Symptomatic medication differentially affects performance on two cognitive tests in PD. After acute treatment, core Stroop measures improved, Stroop interference was unchanged, and SDMT performance worsened, likely reflecting complex changes in processing speed and executive function related to acute treatment. When considering motor symptom therapies in PD, an individual's cognitive demands and expectations, especially regarding executive function, should be considered.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis

OBJECTIVE

This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches.

METHODS

Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm.

RESULTS

Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen.

CONCLUSIONS

The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Insertional effect following electrode implantation: an underreported but important phenomenon

Deep brain stimulation has revolutionized the treatment of movement disorders and is gaining momentum in the treatment of several other neuropsychiatric disorders. In almost all applications of this therapy, the insertion of electrodes into the target has been shown to induce some degree of clinical improvement prior to stimulation onset. Disregarding this phenomenon, commonly referred to as 'insertional effect', can lead to biased results in clinical trials, as patients receiving sham stimulation may still experience some degree of symptom amelioration. Similar to the clinical scenario, an improvement in behavioural performance following electrode implantation has also been reported in preclinical models. From a neurohistopathologic perspective, the insertion of electrodes into the brain causes an initial trauma and inflammatory response, the activation of astrocytes, a focal release of gliotransmitters, the hyperexcitability of neurons in the vicinity of the implants, as well as neuroplastic and circuitry changes at a distance from the target. Taken together, it would appear that electrode insertion is not an inert process, but rather triggers a cascade of biological processes, and, as such, should be considered alongside the active delivery of stimulation as an active part of the deep brain stimulation therapy.

Optogenetic fMRI reveals therapeutic circuits of subthalamic nucleus deep brain stimulation

While deep brain stimulation (DBS) is widely employed for managing motor symptoms in Parkinson's disease (PD), its exact circuit mechanisms remain controversial. To identify the neural targets affected by therapeutic DBS in PD, we analyzed DBS-evoked whole brain activity in female hemi-parkinsonian rats using function magnetic resonance imaging (fMRI). We delivered subthalamic nucleus (STN) DBS at various stimulation pulse repetition rates using optogenetics, allowing unbiased examinations of cell-type specific STN feed-forward neural activity. Unilateral STN optogenetic stimulation elicited pulse repetition rate-dependent alterations of blood-oxygenation-level-dependent (BOLD) signals in SNr (substantia nigra pars reticulata), GP (globus pallidus), and CPu (caudate putamen). Notably, these manipulations effectively ameliorated pathological circling behavior in animals expressing the kinetically faster Chronos opsin, but not in animals expressing ChR2. Furthermore, mediation analysis revealed that the pulse repetition rate-dependent behavioral rescue was significantly mediated by optogenetically induced activity changes in GP and CPu, but not in SNr. This suggests that the activation of GP and CPu are critically involved in the therapeutic mechanisms of STN DBS.

Neuroimaging Biomarkers in Parkinson's Disease

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple systems in the body and is characterized by a variety of motor and non-motor (e.g., psychiatric, autonomic) symptoms. As the fastest growing neurological disorder expected to affect over 12 million people globally by 2040 (Dorsey, Bloem JAMA Neurol 75(1):9-10. https://doi.org/10.1001/jamaneurol.2017.3299 . PMID: 29131880, 2018), PD poses an enormous individual and public health burden. Currently, there are no therapies that can slow down the disease progression in PD, and existing therapies are limited to symptomatic treatment. Importantly, people in the prodromal phase who are at high risk of developing PD can now be identified, which makes disease prevention an achievable goal. An in-depth understanding of the pathological processes in PD is crucial for prevention and treatment development. Advanced multimodal neuroimaging techniques provide unique biomarkers that can further our understanding of PD at multiple levels ranging from neurotransmitters to neural networks. These neuroimaging biomarkers also have value in clinical application, for example, in the differential diagnosis of PD. As the field continues to advance, neuroimaging biomarkers are expected to become more specific, more widely accessible, and can be readily incorporated into translational research for treatment development in PD.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Integrated PET/MRI With 11C-CFT and 18F-FDG for levodopa response difference in Parkinson's disease

AIM

Parkinson's disease is one of the most common neurodegenerative diseases. Excellent levodopa responsiveness has been proposed as a characteristic supporting feature in substantiating the PD diagnosis. However, a small portion of clinically established PD patients shows poor levodopa response. This study aims to investigate brain function alterations of PD patients with poor levodopa responsiveness by PET/MRI.

METHOD

A total of 46 PD patients were recruited. They all completed 11C-CFT PET/MRI scans and the acute levodopa challenge test. Among these 46 PD patients, 42 participants further underwent 18F-FDG PET/MRI scans. Clinical variables regarding demographic data, disease features and cognition scales were also collected. Based on the improvement rate of UPDRS-III, PD patients were divided into non-responders (improvement rate < 33 %) and responders (improvement rate ≥ 33 %). Statistical parametric zapping was performed to analyze molecular imaging. Dopaminergic uptake and metabolism of 70 brain regions were converted to quantitative values and expressed as standard uptake value (SUV). SUV was further normalized by the cerebellum. The resulting SUV ratios and clinical variables were then compared by SPSS.

RESULTS

The difference between levodopa non-responders (n = 17) and responders (n = 29) in the UPDRS III baseline was statistically significant and the former had a lower UPDRS III baseline (19 (10, 32), p＜0.05). In contrast, no statistical difference between these two groups was found in age, gender, disease duration, cognition, motor subtype and Hoehn-Yahr stage. Dopaminergic uptake differences between levodopa non-responders (n = 17) and responders (n = 29) were shown in the left inferior frontal cortex (1.00 ± 0.09 vs 1.07 ± 0.08, p < 0.05 and FDR < 0.2), the right posterior cingulum (1.10 ± 0.10 vs 1.20 ± 0.13, p < 0.05 and FDR < 0.2) and the right insula (1.21 ± 0.12 vs 1.30 ± 0.10, p < 0.05 and FDR < 0.2). The metabolic alterations between levodopa non-responders (n = 16) and responders (n = 26) were shown in the right supplementary motor area (1.30 (1.18, 1.39) vs 1.41 (1.31, 1.53), p < 0.05 and FDR < 0.2), right precuneus (1.37 ± 0.10 vs 1.47 ± 0.18, p < 0.05 and FDR < 0.2), right parietal cortex (1.14 ± 0.15 vs 1.27 ± 0.21, p < 0.05 and FDR < 0.2), right supramarginal gyrus (1.16 (1.12, 1.26) vs 1.25 (1.14, 1.46), p < 0.05 and FDR < 0.2), right postcentral gyrus (1.15 (1.08, 1.32) vs 1.24 (1.17, 1.39), p < 0.05 and FDR < 0.2), medulla (0.75 ± 0.07 vs 0.80 ± 0.07, p < 0.05 and FDR < 0.2), right rolandic operculum (1.25 (1.18, 1.32) vs 1.33 (1.25, 1.50), p < 0.05 and FDR < 0.2), right olfactory (0.95 (0.91, 1.01) vs 1.01 (0.95, 1.15), p < 0.05 and FDR < 0.2), the right insula (1.15 (1.06, 1.22) vs 1.21 (1.12, 1.35), p < 0.05 and FDR < 0.2) and the left cerebellum crus (0.96 (0.91, 1.01) vs 0.92 (0.86, 0.96), p < 0.05 and FDR < 0.2).

CONCLUSIONS

PD patients with poor response to levodopa showed less severe impairment of baseline motor symptoms, more severe dopaminergic deficits in the left inferior frontal, right posterior cingulate cortex and the right insula, and lower metabolism in the right supplementary motor area, right precuneus, right parietal cortex, right supramarginal gyrus, right postcentral gyrus, medulla, right rolandic operculum, right olfactory, the right insula and higher metabolism in the left cerebellum crus.

Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease

Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials.

Effects of STN-DBS surgery on cerebral glucose metabolism and distribution of DAT in Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Subthalamic nucleus (STN) deep brain stimulation (DBS) has been shown to be an effective treatment for PD; however, the effects of this surgery on cerebral metabolism and presynaptic dopamine transporter (DAT) distribution are still being studied.

METHODS

In this study, we included 12 PD patients (6 male and 6 female) who underwent STN-DBS surgery and had both 18 F-FDG and 11 C-CFT PET/CT imaging before and 1 year after the surgery. We used paired t-tests to identify changes in cerebral metabolism and calculated PD-related metabolic covariance pattern (PDRP) scores. We also assessed the uptake of 11 C-CFT in the striatum using striatal-to-occipital ratios (SORs).

RESULTS

One year after surgery, we observed significant reductions in tremor, rigidity, akinesia, postural instability/gait disturbance, and Unified Parkinson's Disease Rating Scale Part III scores (p < .01, p < .001, p < .001, p < .001, and p < .001, respectively). Hamilton Depression Rating Scale and quality of life (PDQ-39 SI) were also significantly reduced (p < .05 and p < .01, respectively). The mean PDRP score decreased by 37% from 13.0 ± 6.6 to 8.2 ± 7.9 after STN-DBS surgery (p < .05). We observed decreased 18 F-FDG uptake in several areas, including the temporal lobe (BA22), thalamus, putamen, and cingulate gyrus (BA24), whereas it was increased in the supplementary motor area, postcentral gyrus, lingual gyrus, and precuneus (p < .05). SORs of 11 C-CFT in the bilateral caudate nucleus and ipsilateral posterior putamen were significantly decreased compared to preoperative levels (p < .05).

CONCLUSION

Our findings suggest that STN-DBS surgery modifies the metabolic network of PD patients and improves motor symptoms, depression, and quality of life. However, it does not prevent the decrease of DAT in striatal areas.

Cerebello-basal Ganglia Networks and Cortical Network Global Efficiency

The cerebellum (CB) and basal ganglia (BG) each have topographically distinct functional subregions that are functionally and anatomically interconnected with cortical regions through discrete thalamic loops and with each other via disynaptic connections, with previous work detailing high levels of functional connectivity between these phylogenetically ancient regions. It was posited that this CB-BG network provides support for cortical systems processing, spanning cognitive, emotional, and motor domains, implying that subcortical network measures are strongly related to cortical network measures (Bostan & Strick, 2018); however, it is currently unknown how network measures within distinct CB-BG networks relate to cortical network measures. Here, 122 regions of interest comprising cognitive and motor CB-BG networks and 7 canonical cortical resting-state were used to investigate whether the integration (quantified using global efficiency, GE) of cognitive CB-BG network (CCBN) nodes and their segregation from motor CB-BG network (MCBN) nodes is related to cortical network GE and segregation in 233 non-related, right-handed participants (Human Connectome Project-1200). CCBN GE positively correlated with GE in the default mode, motor, and auditory networks and MCBN GE positively correlated with GE in all networks, except the default mode and emotional. MCBN segregation was related to motor network segregation. These findings highlight the CB-BG network's potential role in cortical networks associated with executive function, task switching, and verbal working memory. This work has implications for understanding cortical network organization and cortical-subcortical interactions in healthy adults and may help in determining biomarkers and deciphering subcortical differences seen in disease states.

Dystonia and Parkinson's disease: Do they have a shared biology?

Parkinsonism and dystonia co-occur across many movement disorders and are most encountered in the setting of Parkinson's disease. Here we aim to explore the shared neurobiological underpinnings of dystonia and parkinsonism through the clinical lens of the conditions in which these movement disorders can be seen together. Foregrounding the discussion, we briefly review the circuits of the motor system and the neuroanatomical and neurophysiological aspects of motor control and highlight their relevance to the proposed pathophysiology of parkinsonism and dystonia. Insight into shared biology is then sought from dystonia occurring in PD and other forms of parkinsonism including those disorders in which both can be co-expressed simultaneously. We organize these within a biological schema along with important questions to be addressed in this space.

The muscarinic M4 acetylcholine receptor exacerbates symptoms of movement disorders

Barbeau's seesaw hypothesis of dopamine-acetylcholine balance has predominated movement disorders literature for years. Both the simplicity of the explanation and the matching efficacy of anticholinergic treatment in movement disorders seem to support this hypothesis. However, evidence from translational and clinical studies in movement disorders indicates that many features of this simple balance are lost, broken, or absent from movement disorders models or in imaging studies of patients with these disorders. This review reappraises the dopamine-acetylcholine balance hypothesis in light of recent evidence and describes how the Gαi/o coupled muscarinic M4 receptor acts in opposition to dopamine signaling in the basal ganglia. We highlight how M4 signaling can ameliorate or exacerbate movement disorders symptoms and physiological correlates of these symptoms in specific disease states. Furthermore, we propose future directions for investigation of this mechanisms to fully understand the potential efficacy of M4 targeting therapeutics in movement disorders. Overall, initial evidence suggest that M4 is a promising pharmaceutical target to ameliorate motor symptoms of hypo- and hyper-dopaminergic disorders.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

Functional brain networks in the evaluation of patients with neurodegenerative disorders

Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.

Cerebellar and basal ganglia structural connections in humans: Effect of aging and relation with memory and learning

Introduction

The cerebellum and basal ganglia were initially considered anatomically distinct regions, each connected via thalamic relays which project to the same cerebral cortical targets, such as the motor cortex. In the last two decades, transneuronal viral transport studies in non-human primates showed bidirectional connections between the cerebellum and basal ganglia at the subcortical level, without involving the cerebral cortical motor areas. These findings have significant implications for our understanding of neurodevelopmental and neurodegenerative diseases. While these subcortical connections were established in smaller studies on humans, their evolution with natural aging is less understood.

Methods

In this study, we validated and expanded the previous findings of the structural connectivity within the cerebellum-basal ganglia subcortical network, in a larger dataset of 64 subjects, across different age ranges. Tractography and fixel-based analysis were performed on the 3 T diffusion-weighted dataset using Mrtrix3 software, considering fiber density and cross-section as indicators of axonal integrity. Tractography of the well-established cerebello-thalamo-cortical tract was conducted as a control. We tested the relationship between the structural white matter integrity of these connections with aging and with the performance in different domains of Addenbrooke's Cognitive Examination.

Results

Tractography analysis isolated connections from the dentate nucleus to the contralateral putamen via the thalamus, and reciprocal tracts from the subthalamic nucleus to the contralateral cerebellar cortex via the pontine nuclei. Control tracts of cerebello-thalamo-cortical tracts were also isolated, including associative cerebello-prefrontal tracts. A negative linear relationship was found between the fiber density of both the ascending and descending cerebellum-basal ganglia tracts and age. Considering the cognitive assessments, the fiber density values of cerebello-thalamo-putaminal tracts correlated with the registration/learning domain scores. In addition, the fiber density values of cerebello-frontal and subthalamo-cerebellar (Crus II) tracts correlated with the cognitive assessment scores from the memory domain.

Conclusion

We validated the structural connectivity within the cerebellum-basal ganglia reciprocal network, in a larger dataset of human subjects, across wider age range. The structural features of the subcortical cerebello-basal ganglia tracts in human subjects display age-related neurodegeneration. Individual morphological variability of cerebellar tracts to the striatum and prefrontal cortex was associated with different cognitive functions, suggesting a functional contribution of cerebellar tracts to cognitive decline with aging. This study offers new perspectives to consider the functional role of these pathways in motor learning and the pathophysiology of movement disorders involving the cerebellum and striatum.

Sensorimotor network connectivity correlates with motor improvement after repetitive transcranial magnetic stimulation in patients with Parkinson's disease

BACKGROUND

Emerging evidence suggests that repetitive transcranial magnetic stimulation (rTMS) generally improves Parkinson's disease (PD) motor symptoms. However, personal responses to rTMS might be different. In this study, we explore the connectivity changes in PD patients with different responses to rTMS.

METHODS

Among PD patients, 25 were treated with 10Hz-rTMS and seven were with sham rTMS over the supplementary motor area for 10 days. Resting-state functional connectivity magnetic resonance imaging (rs-fMRI) was performed in PD patients before and after rTMS stimulation. Neuropsychological scales such as Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) were collected synchronously with rs-fMRI. To explore the connectivity changes after rTMS, degree centrality was calculated.

RESULTS

13 out of 25 participants were responsive to 10Hz rTMS. Degree centrality patterns in the left sensorimotor regions are primarily responsible for the differences between responsive and non-responsive individuals. Improvement in motor symptoms was substantially related to the baseline degree centrality in the left PreCG and the left PoCG. The performance in distinguishing non-responders from responders was further validated by the ROC analysis utilizing DC characteristics. Lastly, we found that connectivity increased in left PreCG and PoCG in patients with a better response to the rTMS.

CONCLUSION

Taken together, these results suggest that the sensorimotor network is involved in the motor improvement following rTMS treatment, with patients with lower sensorimotor connectivity showing a tendency for greater motor improvement to HF-rTMS.

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

BACKGROUND AND OBJECTIVES

¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson's disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory.

METHODS

We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories.

RESULTS

The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman's rho =0.62, P=0.004).

CONCLUSION

In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages.

Neurobiological effects of deep brain stimulation: A systematic review of molecular brain imaging studies

Deep brain stimulation (DBS) is an established treatment for several brain disorders, including Parkinson's disease, essential tremor, dystonia and epilepsy, and an emerging therapeutic tool in many other neurological and psychiatric disorders. The therapeutic efficacy of DBS is dependent on the stimulation target, but its mechanisms of action are still relatively poorly understood. Investigating these mechanisms is challenging, partly because the stimulation devices and electrodes have limited the use of functional MRI in these patients. Molecular brain imaging techniques, such as positron emission tomography (PET) and single photon emission tomography (SPET), offer a unique opportunity to characterize the whole brain effects of DBS. Here, we investigated the direct effects of DBS by systematically reviewing studies performing an `on' vs `off' contrast during PET or SPET imaging. We identified 62 studies (56 PET and 6 SPET studies; 531 subjects). Approximately half of the studies focused on cerebral blood flow or glucose metabolism in patients Parkinson's disease undergoing subthalamic DBS (25 studies, n = 289), therefore Activation Likelihood Estimation analysis was performed on these studies. Across disorders and stimulation targets, DBS was associated with a robust local increase in ligand uptake at the stimulation site and target-specific remote network effects. Subthalamic nucleus stimulation in Parkinson's disease showed a specific pattern of changes in the motor circuit, including increased ligand uptake in the basal ganglia, and decreased ligand uptake in the primary motor cortex, supplementary motor area and cerebellum. However, there was only a handful of studies investigating other brain disorder and stimulation site combinations (1-3 studies each), or specific neurotransmitter systems, preventing definitive conclusions of the detailed molecular effects of the stimulation in these cases.

Gait‐Related Metabolic Covariance Networks at Rest in Parkinson's Disease

Background

Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted.

Objective

The aim of this study was to identify neural networks of discrete gait impairments in PD.

Methods

Fifty‐five participants with early‐stage PD and 20 age‐matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [¹⁸F]‐2‐fluoro‐2‐deoxyglucose‐positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD.

Results

In PD, we identified two metabolic gait‐related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity.

Conclusions

We have identified two novel gait‐related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

The NADPARK study: A randomized phase I trial of nicotinamide riboside supplementation in Parkinson's disease

We conducted a double-blinded phase I clinical trial to establish whether nicotinamide adenine dinucleotide (NAD) replenishment therapy, via oral intake of nicotinamide riboside (NR), is safe, augments cerebral NAD levels, and impacts cerebral metabolism in Parkinson's disease (PD). Thirty newly diagnosed, treatment-naive patients received 1,000 mg NR or placebo for 30 days. NR treatment was well tolerated and led to a significant, but variable, increase in cerebral NAD levels-measured by ³¹phosphorous magnetic resonance spectroscopy-and related metabolites in the cerebrospinal fluid. NR recipients showing increased brain NAD levels exhibited altered cerebral metabolism, measured by ¹⁸fluoro-deoxyglucose positron emission tomography, and this was associated with mild clinical improvement. NR augmented the NAD metabolome and induced transcriptional upregulation of processes related to mitochondrial, lysosomal, and proteasomal function in blood cells and/or skeletal muscle. Furthermore, NR decreased the levels of inflammatory cytokines in serum and cerebrospinal fluid. Our findings nominate NR as a potential neuroprotective therapy for PD, warranting further investigation in larger trials.

Metabolic imaging and plasticity

Positron emission tomography greatly advanced our understanding on the underlying neural mechanisms of movement disorders. PET with flurodeoxyglucose (FDG) is especially useful as it depicts regional metabolic activity level that can predict patients' symptoms. Multivariate pattern analysis has been used to determine and quantify the co-varying brain networks associated with specific clinical traits of neurodegenerative disease. The result is a biomarker, useful for diagnosis, treatments, and follow up studies. Parkinsonian traits and parkinsonisms are associated with specific spatial pattern of metabolic abnormality useful for differential diagnosis. This approach has also been used for monitoring disease progression and novel treatment responses mostly in Parkinson's disease. In this book chapter, we, illustrate and discuss the significance of the brain networks associated with disease and their modification with neuroplastic changes.

Functional connectivity in Parkinson's disease candidates for deep brain stimulation

This study aimed to identify functional neuroimaging patterns anticipating the clinical indication for deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). A cohort of prospectively recruited patients with PD underwent neurological evaluations and resting-state functional MRI (RS-fMRI) at baseline and annually for 4 years. Patients were divided into two groups: 19 patients eligible for DBS over the follow-up and 41 patients who did not meet the criteria to undergo DBS. Patients selected as candidates for DBS did not undergo surgery at this stage. Sixty age- and sex-matched healthy controls performed baseline evaluations. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity at baseline and at each time point. At baseline, network analysis showed a higher mean nodal strength, local efficiency, and clustering coefficient of the occipital areas in candidates for DBS over time relative to controls and patients not eligible for DBS. The occipital hyperconnectivity pattern was confirmed by regional analysis. At baseline, a decreased functional connectivity between basal ganglia and sensorimotor/frontal networks was found in candidates for DBS compared to patients not eligible for surgery. In the longitudinal analysis, patient candidate for DBS showed a progressively decreased topological brain organization and functional connectivity, mainly in the posterior brain networks, and a progressively increased connectivity of basal ganglia network compared to non-candidates for DBS. RS-fMRI may support the clinical indication to DBS and could be useful in predicting which patients would be eligible for DBS in the earlier stages of PD.

Emerging Neuroimaging Biomarkers Across Disease Stage in Parkinson Disease: A Review

Importance

Imaging biomarkers in Parkinson disease (PD) are increasingly important for monitoring progression in clinical trials and also have the potential to improve clinical care and management. This Review addresses a critical need to make clear the temporal relevance for diagnostic and progression imaging biomarkers to be used by clinicians and researchers over the clinical course of PD. Magnetic resonance imaging (diffusion imaging, neuromelanin-sensitive imaging, iron-sensitive imaging, T1-weighted imaging), positron emission tomography/single-photon emission computed tomography dopaminergic, serotonergic, and cholinergic imaging as well as metabolic and cerebral blood flow network neuroimaging biomarkers in the preclinical, prodromal, early, and moderate to late stages are characterized.

Observations

If a clinical trial is being carried out in the preclinical and prodromal stages, potentially useful disease-state biomarkers include dopaminergic imaging of the striatum; metabolic imaging; free-water, neuromelanin-sensitive, and iron-sensitive imaging in the substantia nigra; and T1-weighted structural magnetic resonance imaging. Disease-state biomarkers that can distinguish atypical parkinsonisms are metabolic imaging, free-water imaging, and T1-weighted imaging; dopaminergic imaging and other molecular imaging track progression in prodromal patients, whereas other established progression biomarkers need to be evaluated in prodromal cohorts. Progression in early-stage PD can be monitored using dopaminergic imaging in the striatum, metabolic imaging, and free-water and neuromelanin-sensitive imaging in the posterior substantia nigra. Progression in patients with moderate to late-stage PD can be monitored using free-water imaging in the anterior substantia nigra, R2* of substantia nigra, and metabolic imaging. Cortical thickness and gyrification might also be useful markers or predictors of progression. Dopaminergic imaging and free-water imaging detect progression over 1 year, whereas other modalities detect progression over 18 months or longer. The reliability of progression biomarkers varies with disease stage, whereas disease-state biomarkers are relatively consistent in individuals with preclinical, prodromal, early, and moderate to late-stage PD.

Conclusions and Relevance

Imaging biomarkers for various stages of PD are readily available to be used as outcome measures in clinical trials and are potentially useful in multimodal combination with routine clinical assessment. This Review provides a critically important template for considering disease stage when implementing diagnostic and progression biomarkers in both clinical trials and clinical care settings.

The role of neuroimaging in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Two hallmarks of PD are the accumulation of alpha-synuclein and the loss of dopaminergic neurons in the brain. There is no cure for PD, and all existing treatments focus on alleviating the symptoms. PD diagnosis is also based on the symptoms, such as abnormalities of movement, mood, and cognition observed in the patients. Molecular imaging methods such as magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) can detect objective alterations in the neurochemical machinery of the brain and help diagnose and study neurodegenerative diseases. This review addresses the application of functional MRI, PET, and SPECT in PD patients. We provide an overview of the imaging targets, discuss the rationale behind target selection, the agents (tracers) with which the imaging can be performed, and the main findings regarding each target's state in PD. Molecular imaging has proven itself effective in supporting clinical diagnosis of PD and has helped reveal that PD is a heterogeneous disorder, which has important implications for the development of future therapies. However, the application of molecular imaging for early diagnosis of PD or for differentiation between PD and atypical parkinsonisms has remained challenging. The final section of the review is dedicated to new imaging targets with which one can detect the PD-related pathological changes upstream from dopaminergic degeneration. The foremost of those targets is alpha-synuclein. We discuss the progress of tracer development achieved so far and challenges on the path toward alpha-synuclein imaging in humans.

Subthalamic and Pallidal Stimulations in Patients with Parkinson's Disease: Common and Dissociable Connections

OBJECTIVE

The subthalamic nucleus (STN) and internal globus pallidus (GPi) are the most effective targets in deep brain stimulation (DBS) for Parkinson's disease (PD). However, the common and specific effects on brain connectivity of stimulating the 2 nuclei remain unclear.

METHODS

Patients with PD receiving STN-DBS (n = 27, 6 women, mean age 64.8 years) or GPi-DBS (n = 28, 13 women, mean age 64.6 years) were recruited for resting-state functional magnetic resonance imaging to assess the effects of STN-DBS and GPi-DBS on brain functional dynamics.

RESULTS

The functional connectivity both between the somatosensory-motor cortices and thalamus, and between the somatosensory-motor cortices and cerebellum decreased in the DBS-on state compared with the off state (p < 0.05). The changes in thalamocortical connectivity correlated with DBS-induced motor improvement (p < 0.05) and were negatively correlated with the normalized intersection volume of tissues activated at both DBS targets (p < 0.05). STN-DBS modulated functional connectivity among a wider range of brain areas than GPi-DBS (p = 0.009). Notably, only STN-DBS affected connectivity between the postcentral gyrus and cerebellar vermis (p < 0.001) and between the somatomotor and visual networks (p < 0.001).

INTERPRETATION

Our findings highlight common alterations in the motor pathway and its relationship with the motor improvement induced by both STN- and GPi-DBS. The effects on cortico-cerebellar and somatomotor-visual functional connectivity differed between groups, suggesting differentiated neural modulation of the 2 target sites. Our results provide mechanistic insight and yield the potential to refine target selection strategies for focal brain stimulation in PD. ANN NEUROL 2021.

Cognition-Related Functional Topographies in Parkinson's Disease: Localized Loss of the Ventral Default Mode Network

Cognitive dysfunction in Parkinson's disease (PD) is associated with increased expression of the PD cognition-related pattern (PDCP), which overlaps with the normal default mode network (DMN). Here, we sought to determine the degree to which the former network represents loss of the latter as a manifestation of the disease process. To address this, we first analyzed metabolic images (fluorodeoxyglucose positron emission tomography [PET]) from a large PD sample with varying cognitive performance. Cognitive impairment in these patients correlated with increased PDCP expression as well as DMN loss. We next determined the spatial relationship of the 2 topographies at the subnetwork level. To this end, we analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from an independent population. This approach uncovered a significant PD cognition-related network that resembled previously identified PET- and rs-fMRI-based PDCP topographies. Further analysis revealed selective loss of the ventral DMN subnetwork (precuneus and posterior cingulate cortex) in PD, whereas the anterior and posterior components were not affected by the disease. Importantly, the PDCP also included a number of non-DMN regions such as the dorsolateral prefrontal and medial temporal cortex. The findings show that the PDCP is a reproducible cognition-related network that is topographically distinct from the normal DMN.

Stimulation of the Subthalamic Nucleus Changes Cortical-Subcortical Blood Flow Patterns During Speech: A Positron Emission Tomography Study

Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for Parkinson's disease (PD) but can have an adverse effect on speech. In normal speakers and in those with spinocerebellar ataxia, an inverse relationship between regional cerebral blood flow (rCBF) in the left inferior frontal (IFG) region and the right caudate (CAU) is associated with speech rate. This pattern was examined to determine if it was present in PD, and if so, whether it was altered by STN-DBS.

Methods: Positron Emission Tomography (PET) measured rCBF during speech in individuals with PD not treated with STN-DBS (n = 7), and those treated with bilateral STN-DBS (n = 7). Previously reported results from non-PD control subjects (n = 16) were reported for comparison. The possible relationships between speech rate during scanning and data from the left and right IFG and CAU head regions were investigated using a step-wise multiple linear regression to identify brain regions that interacted to predict speech rate.

Results: The multiple linear regression analysis replicated previously reported predictive coefficients for speech rate involving the left IFG and right CAU regions. However, the relationships between these predictive coefficients and speech rates were abnormal in both PD groups. In PD who had not received STN-DBS, the right CAU coefficient decreased normally with increasing speech rate but the left IFG coefficient abnormally decreased. With STN-DBS, this pattern was partially normalized with the addition of a left IFG coefficient that increased with speech rate, as in normal controls, but the abnormal left IFG decreasing coefficient observed in PD remained. The magnitudes of both cortical predictive coefficients but not the CAU coefficient were exaggerated with STN-DBS.

Conclusions: STN-DBS partially corrects the abnormal relationships between rCBF and speech rate found in PD by introducing a left IFG subregion that increases with speech rate, but the conflicting left IFG subregion response remained. Conflicting IFG responses may account for some of the speech problems observed after STN-DBS. Cortical and subcortical regions may be differentially affected by STN-DBS.

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning

Commonly used for Parkinson’s disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Deep brain stimulation programming for Parkinson’s disease entails the assessment of a large number of possible simulation settings, requiring numerous clinic visits after surgery. Here, the authors show that patterns of functional MRI can predict the optimal stimulation settings.

Spatial Covariance of Cholinergic Muscarinic M1 /M4 Receptors in Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is associated with cholinergic dysfunction, although the role of M1 and M4 receptors remains unclear.

OBJECTIVE

To investigate spatial covariance patterns of cholinergic muscarinic M₁ /M₄ receptors in PD and their relationship with cognition and motor symptoms.

METHODS

Some 19 PD and 24 older adult controls underwent ¹²³ I-iodo-quinuclidinyl-benzilate (QNB) (M₁ /M₄ receptor) and ^99m Tc-exametazime (perfusion) single-photon emission computed tomography (SPECT) scanning. We implemented voxel principal components analysis, producing a series of images representing patterns of intercorrelated voxels across individuals. Linear regression analyses derived specific M₁ /M₄ spatial covariance patterns associated with PD.

RESULTS

A cholinergic M₁ /M₄ pattern that converged onto key hubs of the default, auditory-visual, salience, and sensorimotor networks fully discriminated PD patients from controls (F_1,41  = 135.4, P < 0.001). In PD, we derived M₁ /M₄ patterns that correlated with global cognition (r = -0.62, P = 0.008) and motor severity (r = 0.53, P = 0.02). Both patterns emerged with a shared topography implicating the basal forebrain as well as visual, frontal executive, and salience circuits. Further, we found a M₁ /M₄ pattern that predicted global cognitive decline (r = 0.46, P = 0.04) comprising relative decreased binding within default and frontal executive networks.

CONCLUSIONS

Cholinergic muscarinic M₁ /M₄ modulation within key brain networks were apparent in PD. Cognition and motor severity were associated with a similar topography, inferring both phenotypes possibly rely on related cholinergic mechanisms. Relative decreased M₁ /M₄ binding within default and frontal executive networks could be an indicator of future cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Modulating brain networks associated with cognitive deficits in Parkinson's disease

Parkinson's disease (PD) is a relatively well characterised neurological disorder that primarily affects motor and cognitive functions. This paper reviews on how transcranial direct current stimulation (tDCS) can be used to modulate brain networks associated with cognitive deficits in PD. We first provide an overview of brain network abnormalities in PD, by introducing the brain network modulation approaches such as pharmacological interventions and brain stimulation techniques. We then present the potential underlying mechanisms of tDCS technique, and specifically highlight how tDCS can be applied to modulate brain network abnormality associated with cognitive dysfunction among PD patients. More importantly, we address the limitations of existing studies and suggest possible future directions, with the aim of helping researchers to further develop the use of tDCS technique in clinical settings.

Resting-State Functional Connectivity Predicts STN DBS Clinical Response

BACKGROUND

Deep brain stimulation of the subthalamic nucleus is a widely used adjunctive therapy for motor symptoms of Parkinson's disease, but with variable motor response. Predicting motor response remains difficult, and novel approaches may improve surgical outcomes as well as the understanding of pathophysiological mechanisms. The objective of this study was to determine whether preoperative resting-state functional connectivity MRI predicts motor response from deep brain stimulation of the subthalamic nucleus.

METHODS

We collected preoperative resting-state functional MRI from 70 participants undergoing subthalamic nucleus deep brain stimulation. For this cohort, we analyzed the strength of STN functional connectivity with seeds determined by stimulation-induced (ON/OFF) 15 O H2 O PET regional cerebral blood flow differences in a partially overlapping group (n = 42). We correlated STN-seed functional connectivity strength with postoperative motor outcomes and applied linear regression to predict motor outcomes.

RESULTS

Preoperative functional connectivity between the left subthalamic nucleus and the ipsilateral internal globus pallidus correlated with postsurgical motor outcomes (r = -0.39, P = 0.0007), with stronger preoperative functional connectivity relating to greater improvement. Left pallidal-subthalamic nucleus connectivity also predicted motor response to DBS after controlling for covariates.

DISCUSSION

Preoperative pallidal-subthalamic nucleus resting-state functional connectivity predicts motor benefit from deep brain stimulation, although this should be validated prospectively before clinical application. These observations suggest that integrity of pallidal-subthalamic nucleus circuits may be critical to motor benefits from deep brain stimulation. © 2020 International Parkinson and Movement Disorder Society.

Cortical hemodynamic mapping of subthalamic nucleus deep brain stimulation in Parkinsonian patients, using high-density functional near-infrared spectroscopy

Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for idiopathic Parkinson's disease. Despite recent progress, the mechanisms responsible for the technique's effectiveness have yet to be fully elucidated. The purpose of the present study was to gain new insights into the interactions between STN-DBS and cortical network activity. We therefore combined high-resolution functional near-infrared spectroscopy with low-resolution electroencephalography in seven Parkinsonian patients on STN-DBS, and measured cortical haemodynamic changes at rest and during hand movement in the presence and absence of stimulation (the ON-stim and OFF-stim conditions, respectively) in the off-drug condition. The relative changes in oxyhaemoglobin [HbO], deoxyhaemoglobin [HbR], and total haemoglobin [HbT] levels were analyzed continuously. At rest, the [HbO], [HbR], and [HbT] over the bilateral sensorimotor (SM), premotor (PM) and dorsolateral prefrontal (DLPF) cortices decreased steadily throughout the duration of stimulation, relative to the OFF-stim condition. During hand movement in the OFF-stim condition, [HbO] increased and [HbR] decreased concomitantly over the contralateral SM cortex (as a result of neurovascular coupling), and [HbO], [HbR], and [HbT] increased concomitantly in the dorsolateral prefrontal cortex (DLPFC)-suggesting an increase in blood volume in this brain area. During hand movement with STN-DBS, the increase in [HbO] was over the contralateral SM and PM cortices was significantly lower than in the OFF-stim condition, as was the decrease in [HbO] and [HbT] in the DLPFC. Our results indicate that STN-DBS is associated with a reduction in blood volume over the SM, PM and DLPF cortices, regardless of whether or not the patient is performing a task. This particular effect on cortical networks might explain not only STN-DBS's clinical effectiveness but also some of the associated adverse effects.

Opportunities of connectomic neuromodulation

The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

Metabolic network as an objective biomarker in monitoring deep brain stimulation for Parkinson's disease: a longitudinal study

Background

With the advance of subthalamic nucleus (STN) deep brain stimulation (DBS) in the treatment of Parkinson’s disease (PD), it is desired to identify objective criteria for the monitoring of the therapy outcome. This paper explores the feasibility of metabolic network derived from positron emission tomography (PET) with ¹⁸F-fluorodeoxyglucose in monitoring the STN DBS treatment for PD.

Methods

Age-matched 33 PD patients, 33 healthy controls (HCs), 9 PD patients with bilateral DBS surgery and 9 controls underwent ¹⁸F-FDG PET scans. The DBS patients were followed longitudinally to investigate the alternations of the PD-related metabolic covariance pattern (PDRP) expressions.

Results

The PDRP expression was abnormally elevated in PD patients compared with HCs (P < 0.001). For DBS patients, a significant decrease in the Unified Parkinson’s Disease Rating Scale (UPDRS, P = 0.001) and PDRP expression (P = 0.004) was observed 3 months after STN DBS treatment, while a rollback was observed in both UPDRS and PDRP expressions (both P < 0.01) 12 months after treatment. The changes in PDRP expression mediated by STN DBS were generally in line with UPDRS improvement. The graphical network analysis shows increased connections at 3 months and a return at 12 months confirmed by small-worldness coefficient.

Conclusions

The preliminary results demonstrate the potential of metabolic network expression as complimentary objective biomarker for the assessment and monitoring of STN DBS treatment in PD patients.

Clinical Trial Registration ChiCTR-DOC-16008645. http://www.chictr.org.cn/showproj.aspx?proj=13865.